Road distresses such as potholes and speed bumps are numerous and ubiquitous, especially in emerging countries. They may appear unexpectedly and are often the result of poor road maintenance. Intelligent transportation system (ITS) technologies like traffic predictions and simulations can be significantly negatively impacted if the existence of road distresses is ignored.
A method is desired to automate detection of certain road distresses given various readily available information such as road graphs, proven car sensor data (accelerometer and GPS, for example), and traffic flow information. Such a system would enable road maintenance crews and traffic operators to locate road distresses and to improve models for ITS.
A variety of efforts have been made to deal with road distresses, generally with limited success. For example, pothole detection using accelerometer sensors are very ineffective, as driver decisions and maneuvering cause most potholes to be avoided.